matrix.matrix_class

Classes

Matrix

Matrix object generated from a 2D array where each element is an array representing

Module Contents

class matrix.matrix_class.Matrix(rows: list[list[int]])

Matrix object generated from a 2D array where each element is an array representing a row. Rows can contain type int or float. Common operations and information available. >>> rows = [ … [1, 2, 3], … [4, 5, 6], … [7, 8, 9] … ] >>> matrix = Matrix(rows) >>> print(matrix) [[1. 2. 3.]

[4. 5. 6.] [7. 8. 9.]]

Matrix rows and columns are available as 2D arrays >>> matrix.rows [[1, 2, 3], [4, 5, 6], [7, 8, 9]] >>> matrix.columns() [[1, 4, 7], [2, 5, 8], [3, 6, 9]]

Order is returned as a tuple >>> matrix.order (3, 3)

Squareness and invertability are represented as bool >>> matrix.is_square True >>> matrix.is_invertable() False

Identity, Minors, Cofactors and Adjugate are returned as Matrices. Inverse can be a Matrix or Nonetype >>> print(matrix.identity()) [[1. 0. 0.]

[0. 1. 0.] [0. 0. 1.]]

>>> print(matrix.minors())
[[-3. -6. -3.]
 [-6. -12. -6.]
 [-3. -6. -3.]]
>>> print(matrix.cofactors())
[[-3. 6. -3.]
 [6. -12. 6.]
 [-3. 6. -3.]]
>>>  # won't be apparent due to the nature of the cofactor matrix
>>> print(matrix.adjugate())
[[-3. 6. -3.]
 [6. -12. 6.]
 [-3. 6. -3.]]
>>> matrix.inverse()
Traceback (most recent call last):
    ...
TypeError: Only matrices with a non-zero determinant have an inverse

Determinant is an int, float, or Nonetype >>> matrix.determinant() 0

Negation, scalar multiplication, addition, subtraction, multiplication and exponentiation are available and all return a Matrix >>> print(-matrix) [[-1. -2. -3.]

[-4. -5. -6.] [-7. -8. -9.]]

>>> matrix2 = matrix * 3
>>> print(matrix2)
[[3. 6. 9.]
 [12. 15. 18.]
 [21. 24. 27.]]
>>> print(matrix + matrix2)
[[4. 8. 12.]
 [16. 20. 24.]
 [28. 32. 36.]]
>>> print(matrix - matrix2)
[[-2. -4. -6.]
 [-8. -10. -12.]
 [-14. -16. -18.]]
>>> print(matrix ** 3)
[[468. 576. 684.]
 [1062. 1305. 1548.]
 [1656. 2034. 2412.]]

Matrices can also be modified >>> matrix.add_row([10, 11, 12]) >>> print(matrix) [[1. 2. 3.]

[4. 5. 6.] [7. 8. 9.] [10. 11. 12.]]

>>> matrix2.add_column([8, 16, 32])
>>> print(matrix2)
[[3. 6. 9. 8.]
 [12. 15. 18. 16.]
 [21. 24. 27. 32.]]
>>> print(matrix *  matrix2)
[[90. 108. 126. 136.]
 [198. 243. 288. 304.]
 [306. 378. 450. 472.]
 [414. 513. 612. 640.]]
__add__(other: Matrix) → Matrix
__eq__(other: object) → bool
__mul__(other: Matrix | float) → Matrix
__ne__(other: object) → bool
__neg__() → Matrix
__pow__(other: int) → Matrix
__repr__() → str
__str__() → str
__sub__(other: Matrix) → Matrix
add_column(column: list[int], position: int | None = None) → None
add_row(row: list[int], position: int | None = None) → None
adjugate() → Matrix
cofactors() → Matrix
columns() → list[list[int]]
determinant() → int
classmethod dot_product(row: list[int], column: list[int]) → int
get_cofactor(row: int, column: int) → int
get_minor(row: int, column: int) → int
identity() → Matrix
inverse() → Matrix
is_invertable() → bool
minors() → Matrix
property is_square: bool
property num_columns: int
property num_rows: int
property order: tuple[int, int]